Skip to main content
SpringerLink
Log in

Spectrum Sharing of Drone Networks

  • Living reference work entry
  • First Online:
Handbook of Cognitive Radio

  • 137 Accesses

Abstract

Drone networks are aerial base stations that can be used to support cellular networks. The underlay spectrum sharing between the three-dimensional (3D) drone small cells (DSCs) downlink network modeled by a 3D Poisson point process and traditional cellular networks modeled by a 2D Poisson point process is introduced. To maximize the DSC network throughput while satisfying the cellular network efficiency constraint, the optimal density of DSC aerial base stations is discussed. The maximum throughput of the DSC user increases almost linearly with the increase of the DSC outage constraint. Effects of directional transmission on DSC networks is further discussed. Besides density control, power and beam control can also be applied in the spectrum sharing between unmanned aerial vehicle (UAV) network and ground network. With the mobility pattern information of UAVs, the delay-tolerant transmissions can be constructed and multiple transmission modes are implemented to carry various types of traffic. Exploiting cognition capability on mobility, UAV network can provide high quality of information services in the highly dynamic environment with limited resources.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    Reader could refer to (8) and (9) in [10] for the details of air-to-ground channel model.

References

  1. Al-Hourani A, Kandeepan S, Jamalipour A (2014) Modeling air-to-ground path loss for low altitude platforms in urban environments. In: IEEE global communication conference (GLOBECOM), Austin, pp 2898–2904. https://doi.org/10.1109/GLOCOM.2014.7037248

  2. Al-Hourani A, Kandeepan S, Lardner S (2014) Optimal LAP altitude for maximum coverage. IEEE Wirel Commun Lett 3(6):569–572. https://doi.org/10.1109/LWC.2014.2342736

    Article  Google Scholar 

  3. Mozaffari M, Saad W, Bennis M, Debbah M (2015) Drone small cells in the clouds: design, deployment and performance analysis. In: IEEE global communication conference (GLOBECOM), San Diego, pp 1–6. https://doi.org/10.1109/GLOCOM.2015.7417609

  4. Lin X et al (2018) The sky is not the limit: LTE for unmanned aerial vehicles. IEEE Commun Mag 56(4):204–210. https://doi.org/10.1109/MCOM.2018.1700643

    Article  Google Scholar 

  5. Federal Aviation Administration (FAA) (2017) UAS traffic management research transition tea plan. Technical report. https://www.faa.gov/uas/research/utm/media/FAA_NASA_UAS_Traffic_Management_Research_Plan.pdf

  6. Wei Z, Wu H, Huang S, Feng Z (2017) Scaling laws of unmanned aerial vehicle network with mobility pattern information. IEEE Commun Lett 21(6):1389–1392. https://doi.org/10.1109/LCOMM.2017.2671861

    Article  Google Scholar 

  7. Cover T, Thomas J (2012) Elements of information theory. Wiley, New York

    MATH  Google Scholar 

  8. Zhang C, Zhang W (2017) Spectrum sharing for drone networks. IEEE J Sel Areas Commun 35(1):136–144. https://doi.org/10.1109/JSAC.2016.2633040

    Google Scholar 

  9. Zhang C, Zhang W (2016) Spectrum sharing in drone small cells. In: Proceedings of IEEE global communication conference (GLOBECOM), Washington. https://doi.org/10.1109/GLOCOM.2016.7842290

  10. Mozaffari M, Saad W, Bennis M, Debbah M (2016) Unmanned aerial vehicle with underlaid device-to-device communications: performance and tradeoffs. IEEE Trans Wirel Commun 15(6):3949–3963. https://doi.org/10.1109/TWC.2016.2531652

    Article  Google Scholar 

  11. Andrews JG, Baccelli F, Ganti RK (2011) A tractable approach to coverage and rate in cellular networks. IEEE Trans Commun 59(11):3122–3134. https://doi.org/10.1109/TCOMM.2011.100411.100541

    Article  Google Scholar 

  12. Bai T, Heath RW Jr (2015) Coverage and rate analysis for millimeter wave cellular networks. IEEE Trans Wirel Commun 14(2):1100–1114. https://doi.org/10.1109/TWC.2014.2364267

    Article  Google Scholar 

  13. Zhang X, Haenggi M (2014) A stochastic geometry analysis of inter-cell interference coordination and intra-cell diversity. IEEE Trans Wirel Commun 13(12):6655–6669. https://doi.org/10.1109/TWC.2014.2339273

    Article  Google Scholar 

  14. Vu M, Devroye N, Tarokh V (2009) On the primary exclusive region of cognitive networks. IEEE Trans Wirel Commun 8:3380–3385. https://doi.org/10.1109/TWC.2009.080454

    Article  Google Scholar 

  15. Bagayoko A, Tortelier P, Fijalkow I (2010) Impact of shadowing on the primary exclusive region in cognitive networks. In: European wireless conference (EW), Lucca, pp 105–110. https://doi.org/10.1109/EW.2010.5483402

  16. Wang Z, Zhang W (2014) Opportunistic spectrum sharing with limited feedback in Poisson cognitive radio networks. IEEE Trans Wirel Commun 13(12):7098–7109. https://doi.org/10.1109/TWC.2014.2363676

    Article  Google Scholar 

  17. Dahama R, Sowerby KW, Rowe GB (2013) Estimating protection distances in spectrum sharing systems. IEEE Trans Signal Process 61(17):4284–4295. https://doi.org/10.1109/TSP.2013.2269901

    Article  Google Scholar 

  18. Wei Z, Feng Z, Zhang Q, Li W (2015) Three regions for space-time spectrum sensing and access in cognitive radio networks. IEEE Trans Veh Technol 64(6):2448–2462. https://doi.org/10.1109/GLOCOM.2012.6503290

    Article  Google Scholar 

  19. Wei Z, Feng Z, Zhang Q, Li W (2015) Three regions for space-time spectrum sensing and access in cognitive radio networks. IEEE Trans Veh Technol 64(6):2448–2462. https://doi.org/10.1109/TVT.2014.2342612

    Article  Google Scholar 

  20. Guo A, Haenggi M (2015) Asymptotic deployment gain: a simple approach to characterize the SINR distribution in general cellular networks. IEEE Trans Commun 63(3):962–976. https://doi.org/10.1109/TCOMM.2014.2387170

    Article  Google Scholar 

  21. Gupta AK, Zhang X, Andrews JG (2015) SINR and throughput scaling in ultradense urban cellular networks. IEEE Wirel Commun Lett 4(6):605–608. https://doi.org/10.1109/LWC.2015.2472404

    Article  Google Scholar 

  22. Lee S, Zhang R, Huang K (2013) Opportunistic wireless energy harvesting in cognitive radio networks. IEEE Trans Wirel Commun 12(9):4788–4799. https://doi.org/10.1109/TWC.2013.072613.130323

    Article  Google Scholar 

  23. Keeler HP, Ross N, Xia A (2015) When do wireless network signals appear Poisson. Available via DIALOG. https://arxiv.org/abs/1411.3757

  24. Andrews JG, Buzzi S, Choi W, Hanly SV, Lozano A, Soong ACK, Zhang JC (2014) What will 5G be? IEEE J Sel Areas Commun 32(6):1065–1082. https://doi.org/10.1109/JSAC.2014.2328098

    Article  Google Scholar 

  25. Carle J, Myoupo JF, Seme D (2001) A basis for 3-D cellular networks. In: Proceedings of the 15th international conference on information networking, Beppu City, pp 631–636. https://doi.org/10.1109/ICOIN.2001.905525

  26. Alam SM, Haas ZJ (2006) Coverage and connectivity in three-dimensional networks. In: Proceedings of the 12th annual international conference on mobile computing and networking, Los Angeles, pp 346–357. https://doi.org/10.1145/1161089.1161128

  27. Zeng Y, Zhang R, Lim TJ (2016) Wireless communications with unmanned aerial vehicles: opportunities and challenges. IEEE Commun Mag 54(5):36–42. https://doi.org/10.1109/MCOM.2016.7470933

    Article  Google Scholar 

  28. Streit RL (2010) Probability generating functional. In: Poisson point processes: imaging, tracking, and sensing. Springer Science & Business Media, Berlin, p 27

    Chapter  Google Scholar 

  29. Zhou L, Yang Z, Zhou S, Zhang W (2018) Coverage probability analysis of UAV cellular networks in Urban environments. In: Proceeding IEEE international conference on communication (ICC), Kansas City

    Google Scholar 

  30. Guo Z, Wei Z, Feng Z, Fan N (2017) Coverage probability of multiple UAVs supported ground network. Electron Lett 53(13):885–887. https://doi.org/10.1049/el.2017.0800

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Electrical Engineering and Telecommunications, The University of New South Wales, Sydney, NSW, Australia

    Chiya Zhang & Wei Zhang

  2. Beijing University of Posts and Telecommunications, Beijing, China

    Zhiqing Wei & Zhiyong Feng

Authors
  1. Chiya Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhiqing Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zhiyong Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Wei Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chiya Zhang .

Editor information

Editors and Affiliations

  1. Electrical Engg Bldg, Rm 325, The University of New South Wales, Sydney, NSW, Australia

    Wei Zhang

Section Editor information

  1. School of Electronics Engineering and Computer Science, Peking University, Beijing, China

    Lingyang Song

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Zhang, C., Wei, Z., Feng, Z., Zhang, W. (2019). Spectrum Sharing of Drone Networks. In: Zhang, W. (eds) Handbook of Cognitive Radio . Springer, Singapore. https://doi.org/10.1007/978-981-10-1389-8_35-1

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-1389-8_35-1

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-1389-8

  • Online ISBN: 978-981-10-1389-8

  • eBook Packages: Springer Reference EngineeringReference Module Computer Science and Engineering

Publish with us

Policies and ethics

Search

Navigation